Introduction: Solitary pulmonary nodules (SPNs) are commonly found in imaging technologies, but are plagued by high false-positive rates.
Objective: We aimed to identify metabolic alterations in SPN etiology and diagnosis using less invasive plasma metabolomics and lipidomics.
Methods: In total, 1160 plasma samples were obtained from healthy volunteers (n = 280), benign SPNs (n = 157) and malignant SPNs (stage I, n = 723) patients enrolled from 5 independent centers. Gas chromatography-triple quadrupole mass spectrometry (GC‒MS) and liquid chromatography-Q Exactive Hybrid Quadrupole-Orbitrap mass spectrometry (LC‒MS) were used to analyze the samples for untargeted metabolomics and lipidomics.
Results And Conclusion: GC‒MS-based metabolomics revealed 1336 metabolic features, while LC‒MS-based lipidomics revealed 6088 and 2542 lipid features in the positive and negative ion modes, respectively. The metabolic and lipidic characteristics of healthy vs. benign or malignant SPNs exhibited substantial pattern differences. Of note, benign and malignant SPNs had no significant variations in circulating metabolic and lipidic markers and were validated in four other centers. This study demonstrates evidence of early metabolic alterations that can possibly distinguish SPNs from healthy controls, but not between benign and malignant SPNs.
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http://dx.doi.org/10.1007/s11306-022-01929-0 | DOI Listing |
Best Pract Res Clin Anaesthesiol
March 2024
1400 Holcombe Blvd, FC 13.2000, Houston, TX, 77030, USA. Electronic address:
Lung cancer is among one of the most commonly diagnosed malignancies and is the leading cause of cancer-related mortality in both men and women globally, with an estimated 1.8 million deaths annually. Moreover, it is also the leading cause of cancer related deaths in the United States (U.
View Article and Find Full Text PDFCureus
December 2024
General Surgery, Rajendra Institute of Medical Sciences, Ranchi, IND.
Phyllodes tumor is a type of fibroepithelial neoplasm involving the breast. This tumor is rarely reported in adolescents and the elderly and has a peak incidence in middle-aged women. Histologically, phyllodes tumors are classified as benign, borderline, or malignant.
View Article and Find Full Text PDFFront Endocrinol (Lausanne)
January 2025
Center of Breast and Thyroid Surgery, Department of General Surgery, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Objective: This study aimed to assess the degree of effect of central lymph node dissection on postoperative hypoparathyroidism incidence.
Methods: The incidence of postoperative hypoparathyroidism was compared between patients receiving thyroidectomy with central neck dissection for papillary thyroid carcinoma and those undergoing thyroidectomy for benign thyroid diseases (thyroid follicular adenoma and/or nodular goiter) necessitating surgical intervention.
Results: The incidence of postoperative hypoparathyroidism was not significantly different between the groups of lobe thyroidectomy for benign thyroid diseases and lobe thyroidectomy with ipsilateral central lymph node dissection for papillary thyroid carcinoma (immediate: 9.
Prostate cancer (PC) progresses from benign epithelium through pre-malignant lesions, localized tumors, metastatic dissemination, and castration-resistant stages, with some cases exhibiting phenotype plasticity under therapeutic pressure. However, high-resolution insights into how cell phenotypes evolve across successive stages of PC remain limited. Here, we present the Prostate Cancer Cell Atlas (PCCAT) by integrating ∼710,000 single cells from 197 human samples covering a spectrum of tumor stages.
View Article and Find Full Text PDFFront Oncol
December 2024
Honorary Research Associate, Department of Operations and Quality Management, Durban University of Technology, Durban, South Africa.
Introduction: Lung cancer is one of the main causes of the rising death rate among the expanding population. For patients with lung cancer to have a higher chance of survival and fewer deaths, early categorization is essential. The goal of thisresearch is to enhance machine learning to increase the precision and quality of lung cancer classification.
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